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| { | |
| "metadata": { | |
| "name": "Plotly with IPython - Documentation" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": "Plotly and IPython - Documentation and Examples\n===\n\nBackground\n---\nPlotly ([https://plot.ly](https://plot.ly)) is a collaborative data analysis and graphing platform. Plotly's IPython Graphing Library ([https://plot.ly/python](https://plot.ly)) interfaces Plotly's online graphing tools with your IPython notebook environment. Send data to your Plotly account, embed the graphs in your IPython notebook, and share them in your web browser. Style with code or with our online interface; share your work publicly with a url or privately among other Plotly members; access your graphs from anywhere.\nLearn More\n---\n- A talk and a demo: [Using Plotly and IPython for Scientific Computing](https://www.youtube.com/watch?v=zG8FYPFU9n4&feature=youtu.be&a)\n- Plotly Homepage: [https://plot.ly](https://plot.ly)\n- Plotly APIs for [Python](https://plot.ly/python), [Julia](https://plot.ly/julia), [MATLAB] (https://plot.ly/MATLAB), [R](https://plot.ly/R), [Arduino](https://plot.ly/arduino), [Perl](https://plot.ly/perl) and our [REST protocal](https://plot.ly/REST)\n- Let us know what you think: [chris[at]plot[dot]ly]([mailto:[email protected]])\n" | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": "Import and sign up to plotly\n===\nYou can sign up through the API. We'll generate an temporary password and an API key for you. You can reset your password here: [https://plot.ly/accounts/password/reset/](https://plot.ly/accounts/password/reset/) and you can reset your API key here: [https://plot.ly/api](https://plot.ly/api) under \"Installation Instructions\"" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "import plotly", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 1 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "username = 'xxxxxxx'\nemail = '[email protected]'\n\nres = plotly.signup(username,email)\nprint res", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n" | |
| } | |
| ], | |
| "prompt_number": 4 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "py = plotly.plotly(res['un'], res['api_key'])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 6 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "50 Box Plots with 1 Line" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "from numpy import *\npy.iplot([{'y': random.randn(5), 'type': 'box'} for i in range(50)], layout={'showlegend': False})", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/28/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 48, | |
| "text": "<IPython.core.display.HTML at 0x104cb6510>" | |
| } | |
| ], | |
| "prompt_number": 48 | |
| }, | |
| { | |
| "cell_type": "raw", | |
| "metadata": {}, | |
| "source": "That graph is interactive! Click and drag to zoom, shift-click and drag to pan, double-click to autoscale.\n\nIt's also saved in your newly created plotly account. Click \"view in plotly\" to open it up in our online interface which includes a GUI for styling the graph." | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Concentric Annuli" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "from numpy import *\n\n# fill several concentric annuli with random points of equal density\n# color with the \"hue, saturation, lightness, alpha\" color code (hsla)\n# by keeping the hue, saturation, and alpha channels constant and marching\n# up the lightness channel\n\n\nt = 0.1 # thickness\nradius = arange(t, 5., t) \ndensity = 30.\ndata = []\n\nfor i in range(len(radius)):\n r = radius[i]\n npoints = density * pi * (r**2 - (r-t)**2)\n rand_radius = t*random.rand(npoints)+r\n rand_angle = random.rand(npoints)*2*pi\n x = rand_radius*cos(rand_angle)\n y = rand_radius*sin(rand_angle)\n color = 'hsla(284, 100%, '+str(10+i*90/len(radius))+'%, 0.88)'\n data.append({'x': x, 'y': y, 'type':'scatter','mode':'markers','marker':{'color':color}})\n\nl={'autosize': False,'width': 550, 'height': 550,\n\t'xaxis' : { \"ticks\": \"\", \"gridcolor\": \"white\", \"zerolinecolor\": \"white\", \"linecolor\": \"rgb(0, 0, 0)\", \"linewidth\": 3 },\n\t'yaxis' : { \"ticks\": \"\", \"gridcolor\": \"white\", \"zerolinecolor\": \"white\", \"linecolor\": \"rgb(0, 0, 0)\", \"linewidth\": 3 },\n\t'plot_bgcolor': 'rgb(229,229,229)', 'showlegend': False, 'hovermode': 'closest'}\n\npy.iplot(data,layout=l)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/27/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 47, | |
| "text": "<IPython.core.display.HTML at 0x104cb4810>" | |
| } | |
| ], | |
| "prompt_number": 47 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Simple Line Plots" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "x0 = [1,2,3,4]; y0 = [10,15,13,17]\nx1 = [2,3,4,5]; y1 = [16,5,11,9]\npy.iplot(x0, y0, x1, y1)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\nHigh five! You successfuly sent some data to your account on plotly. View your plot in your browser at https://plot.ly/~chriddyp/1 or inside your plot.ly account where it is named 'plot from API (1)'\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/1/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 8, | |
| "text": "<IPython.core.display.HTML at 0x1040beed0>" | |
| } | |
| ], | |
| "prompt_number": 8 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "py.verbose=False", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 9 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "trace0 = {'x': [1,2,3,4], \n 'y': [10,15,13,17],\n 'type': 'scatter', \n 'mode': 'markers'}\n\ntrace1 = {'x': [2,3,4,5], \n 'y': [16,5,11,9],\n 'type': 'scatter', \n 'mode': 'lines'}\n\ntrace2 = {'x': [1,2,3,4], \n 'y': [12,9,15,12],\n 'type': 'scatter', \n 'mode': 'lines+markers'}\n\npy.iplot([trace0, trace1, trace2])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/2/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 10, | |
| "text": "<IPython.core.display.HTML at 0x102c56f10>" | |
| } | |
| ], | |
| "prompt_number": 10 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Fully Styled Line Plot" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "x1 = [1,2,3]; y1 = [4,5,6]\nx2 = [1,2,3]; y2 = [2,10,12]\n \n# plotly's data dictionaries\ntrace1 = {'x': x1,\n 'y': y1,\n \"name\":\"Experiment\",\n \"type\":\"scatter\",\n \"line\":{\n \"color\":\"rgb(3,78,123)\", \n \"width\":6,\n \"dash\":\"dot\"\n },\n \"marker\":{\n \"opacity\":1.0,\n \"symbol\":\"square\",\n \"size\":12,\n \"color\":\"rgb(54,144,192)\",\n \"line\":{\n \"width\":3,\n \"color\":\"darkblue\"\n }\n }\n}\n\ntrace2 = {\"x\":x2,\n \"y\":y2,\n \"name\":\"Control\", \n \"type\":\"scatter\",\n \"line\":{\n \"color\":\"purple\",\n \"width\":4,\n \"dash\":\"dashdot\"\n },\n \"marker\":{\n \"opacity\":0.9,\n \"symbol\":\"cross\",\n \"size\":16,\n \"color\":\"fuchsia\",\n \"line\":{\n \"color\":\"\",\n \"width\":0\n },\n }\n}\n\npy.iplot([trace1, trace2])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/3/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 11, | |
| "text": "<IPython.core.display.HTML at 0x1040d2d50>" | |
| } | |
| ], | |
| "prompt_number": 11 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Basic Area Plot" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# basic-area \ntrace0 = {'x': [1,2,3,4], \n 'y': [0, 2, 3, 5],\n 'fill': 'tozeroy'}\n\ntrace1 = {'x': [1,2,3,4], \n 'y': [3,5,1,7],\n 'fill': 'tonexty'}\n\npy.iplot([trace0, trace1])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/4/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 13, | |
| "text": "<IPython.core.display.HTML at 0x1040d52d0>" | |
| } | |
| ], | |
| "prompt_number": 13 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Bar Charts" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# basic-bar \nx0 = ['giraffes', 'orangutans', 'monkeys'];\ny0 = [20, 14, 23];\ndata = {'x': x0, 'y': y0,\n 'type': 'bar'}\npy.iplot([data])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/5/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 14, | |
| "text": "<IPython.core.display.HTML at 0x1002eb7d0>" | |
| } | |
| ], | |
| "prompt_number": 14 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# grouped-bar \ncategories = ['giraffes', 'orangutans', 'monkeys']; \nSF = {'name': 'SF Zoo', \n 'x': categories, \n 'y': [20, 14, 23],\n 'type': 'bar'}\nLA = {'name': 'LA Zoo',\n 'x': categories, \n 'y': [12,18,29],\n 'type': 'bar'}\nlayout = {\n 'barmode': 'group',\n 'xaxis': {'type': 'category'},\n 'categories': categories}\npy.iplot([LA, SF], layout=layout)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/6/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 16, | |
| "text": "<IPython.core.display.HTML at 0x1040d5390>" | |
| } | |
| ], | |
| "prompt_number": 16 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "layout = {'barmode': 'stack', \n 'xaxis': {'type': 'category'},\n 'categories': categories}\npy.iplot([SF, LA], layout=layout)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/7/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 17, | |
| "text": "<IPython.core.display.HTML at 0x104c86fd0>" | |
| } | |
| ], | |
| "prompt_number": 17 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "categories=['giraffes', 'orangutans', 'monkeys']\nSF = {'name': 'SF Zoo', \n 'x': categories, \n 'y': [20, 14, 23],\n 'type': 'bar',\n 'marker':{\n 'color': 'orange',\n 'line': {'color': 'grey', \n 'width': 3}}\n }\n\nLA = {'name': 'LA Zoo',\n 'x': categories, \n 'y': [12,18,29],\n 'type': 'bar',\n 'marker': {'color': 'rgb(111, 168, 220)',\n 'line': {'color': 'grey',\n 'width': 3}}\n }\n\nlayout = {\n 'title': 'Animal Population',\n 'barmode': 'group',\n 'yaxis': {'name': '# of animals (thousands)'},\n 'xaxis': {'type': 'category'},\n 'categories': categories,\n 'bargap': 0.25,\n 'bargroupgap': 0.3,\n 'bardir': 'v'}\n\npy.iplot([LA, SF], layout=layout)\n", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/8/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 20, | |
| "text": "<IPython.core.display.HTML at 0x104c86210>" | |
| } | |
| ], | |
| "prompt_number": 20 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Error Bars" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# Error Bars \ndata = {'x': [0,1,2],\n 'y': [6,10,2],\n 'error_y': {'type': 'data',\n 'array': [1, 2, 3],\n 'visible': True}}\npy.iplot([data])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/9/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 22, | |
| "text": "<IPython.core.display.HTML at 0x10073c7d0>" | |
| } | |
| ], | |
| "prompt_number": 22 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# percent-error-bar \ndata = {'x': [0,1,2],\n 'y': [6,8,4],\n 'error_y': {'type': 'percent',\n 'value': 50,\n 'visible': True}}\npy.iplot([data])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/10/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 23, | |
| "text": "<IPython.core.display.HTML at 0x104c943d0>" | |
| } | |
| ], | |
| "prompt_number": 23 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "categories = ['Trial 1', 'Trial 2', 'Trial 3']\ncontrol = {'x': categories, \n 'y': [3, 6, 4],\n 'type': 'bar',\n 'marker':{'color': 'rgb(74, 134, 232)'},\n 'error_y': {'type': 'data',\n 'array': [1, 0.5, 1.5],\n 'visible': True,\n 'color': 'rgb(67, 67, 67)'}}\nexp = {'x': categories,\n 'y': [4, 7, 3],\n 'type': 'bar',\n 'marker':{'color':'rgb(111, 168, 220)'},\n 'error_y': {'type': 'data',\n 'array': [0.5, 1, 2],\n 'visible': True,\n 'color': 'rgb(67, 67, 67)'}}\nlayout = {'barmode': 'group'}\n\npy.iplot([control, exp], layout=layout)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/11/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 25, | |
| "text": "<IPython.core.display.HTML at 0x104ac1790>" | |
| } | |
| ], | |
| "prompt_number": 25 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Box Plots" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# basic-box-plot \nbox1 = {'y': [0, 1, 2, 4],\n 'type': 'box'}\nbox2 = {'y': [1,2,4,5,8],\n 'type': 'box'}\npy.iplot([box1, box2])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/12/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 26, | |
| "text": "<IPython.core.display.HTML at 0x104ac1990>" | |
| } | |
| ], | |
| "prompt_number": 26 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# jitter \nfrom numpy import *\nbox = {'y': random.randn(50),\n 'type': 'box',\n 'boxpoints': 'all',\n 'jitter': 0.3, \n 'pointpos': -1.8} \npy.iplot([box])\n", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/13/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 27, | |
| "text": "<IPython.core.display.HTML at 0x1040d53d0>" | |
| } | |
| ], | |
| "prompt_number": 27 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Histograms" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "from numpy import *\nx = random.randn(500) # normally distributed vector\ndata = {'x': x,\n 'type': 'histogramx'}\npy.iplot([data])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/14/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 28, | |
| "text": "<IPython.core.display.HTML at 0x104c94790>" | |
| } | |
| ], | |
| "prompt_number": 28 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# stacked-histo \nfrom numpy import *\nx0 = random.randn(500)\nx1 = random.randn(500)+1\ndata0 = {'x': x0,\n 'type': 'histogramx'}\ndata1 = {'x': x1,\n 'type': 'histogramx'}\nlayout = {'barmode': 'stack'}\npy.iplot([data0, data1], layout=layout)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/15/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 29, | |
| "text": "<IPython.core.display.HTML at 0x104c94990>" | |
| } | |
| ], | |
| "prompt_number": 29 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "layout = {'barmode': 'overlay'} \npy.iplot([data0, data1], layout=layout)\n", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/16/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 30, | |
| "text": "<IPython.core.display.HTML at 0x104c86b50>" | |
| } | |
| ], | |
| "prompt_number": 30 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# style-histo \nfrom numpy import *\nx0 = random.randn(500)\nx1 = random.randn(500)+1\ndata0 = {'x': x0,\n 'type': 'histogramx',\n 'name': 'control',\n 'marker':{\n 'color': 'rgba(255,0,255,0.75)',\n 'opacity': 0.75,\n },\n 'autobinx': False,\n 'xbins':{\n 'start': -3.2,\n 'end': 2.8,\n 'size': 0.2\n },\n 'histnorm': 'count'\n}\ndata1 = {'x': x1,\n 'name': 'experiment',\n 'type': 'histogramx',\n 'marker':{\n 'color': 'rgba(255, 217, 102,0.75)',\n 'opacity': 0.75},\n 'autobinx': False,\n 'xbins':{\n 'start': -1.8,\n 'end': 4.2,\n 'size': 0.2\n }\n }\n\nlayout = {'barmode': 'overlay',\n 'bargap': 0.25,\n 'bargroupgap': 0.3,\n 'bardir': 'v',\n 'title': 'Sampled Results',\n 'xaxis': {'title': 'Value'},\n 'yaxis': {'title': 'Count'}} \npy.iplot([data0, data1], layout=layout)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/19/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 39, | |
| "text": "<IPython.core.display.HTML at 0x104c94b50>" | |
| } | |
| ], | |
| "prompt_number": 39 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "2D Histograms" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "from numpy import *\nx = random.randn(500)\ny = random.randn(500)+1\ndata = {'x': x, 'y': y,\n 'type': 'histogram2d'}\npy.iplot([data])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/20/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 40, | |
| "text": "<IPython.core.display.HTML at 0x104c86990>" | |
| } | |
| ], | |
| "prompt_number": 40 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "from numpy import *\nx = random.randn(500)\ny = random.randn(500)+1\ndata = {'x': x, \n 'y': y,\n 'type': 'histogram2d',\n 'autobinx': False,\n 'xbins': {\n 'start': -3,\n 'end': 3,\n 'size': 0.1\n },\n 'autobiny': False,\n 'ybins': {\n 'start': -2.5,\n 'end': 4,\n 'size': 0.1\n },\n 'scl': [[0,\"rgb(12,51,131)\"],\\\n [0.25,\"rgb(10,136,186)\"],\\\n [0.5,\"rgb(242,211,56)\"],\\\n [0.75,\"rgb(242,143,56)\"],\\\n [1,\"rgb(217,30,30)\"]],\n 'histnorm': 'probability'\n}\n\nlayout = {\n 'xaxis':{\n 'range':[-2,2],\n 'autorange':False\n },'yaxis':{\n 'range':[-1,3],\n 'autorange':False \n },\n 'width':520,'height':380,\n 'autosize':False\n }\n\npy.iplot([data],layout=layout)", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/21/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 41, | |
| "text": "<IPython.core.display.HTML at 0x104ac1a90>" | |
| } | |
| ], | |
| "prompt_number": 41 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Heatmaps" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "# basic-heatmap \nz = [[1., 20., 30 ],\\\n [20., 1., 60 ],\\\n [30., 60., 1.]]\ndata = {'z': z,\n 'type': 'heatmap'}\npy.iplot([data])\n", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/22/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 42, | |
| "text": "<IPython.core.display.HTML at 0x104c94250>" | |
| } | |
| ], | |
| "prompt_number": 42 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "x = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']\ny = ['Morning', 'Afternoon', 'Evening']\nz = [[1., 20., 30, 50, 1],\\\n [20., 1., 60, 80, 30 ],\\\n [30., 60., 1., -10, 20]]\ndata = {'x': x,\n 'y': y,\n 'z': z,\n 'type': 'heatmap'}\npy.iplot([data])\n", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/23/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 43, | |
| "text": "<IPython.core.display.HTML at 0x104ac1ad0>" | |
| } | |
| ], | |
| "prompt_number": 43 | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": "Mixed Types" | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "from numpy import *\nx0 = linspace(0, 5, 15)\ny0 = sin(x0) + random.rand(15)\ndata0 = {'x': x0,'y': y0,\n 'type': 'scatter'}\n\nx1 = [0, 1, 2, 3, 4, 5]\ny1 = [1, 0.5, 0.7, -1.2, 0.3, 0.4]\ndata1 = {'x': x1,'y': y1,\n 'type': 'bar'}\n\npy.iplot([data0, data1])", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/24/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 44, | |
| "text": "<IPython.core.display.HTML at 0x104ac19d0>" | |
| } | |
| ], | |
| "prompt_number": 44 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "from numpy import *\n \nx0 = random.randn(100)/5. + 0.5 \ny0 = random.randn(100)/5. + 0.5 \n \nx1 = random.rayleigh(size=80)/7. + 0.1\ny1 = random.rayleigh(size=80)/8. + 1.1\n \ny = concatenate([y0,y1])\nx = concatenate([x0,x1])\n\ndata0 = {'x': x0, 'y': y0, \n 'marker':{'symbol':'circle'},\n 'type': 'scatter', 'mode': 'markers'}\ndata1 = {'x': x1, 'y': y1, \n 'marker':{'symbol':'cross'},\n 'type': 'scatter', 'mode': 'markers'}\n \ndata_hist = {'x': x, 'y': y, \n 'type':'histogram2d'}\n\npy.iplot([data0,data1,data_hist])\n", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": "\n\n" | |
| }, | |
| { | |
| "html": "<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~chriddyp/25/600/600\" width=\"650\"></iframe>", | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 45, | |
| "text": "<IPython.core.display.HTML at 0x104cb6fd0>" | |
| } | |
| ], | |
| "prompt_number": 45 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": "", | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [] | |
| } | |
| ], | |
| "metadata": {} | |
| } | |
| ] | |
| } |
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